Proportion based real time display of statistics and values for selected regular expressions

ABSTRACT

Embodiments are directed towards real time display of event records and extracted values based on at least one extraction rule, such as a regular expression. A user interface may be employed to enable a user to have an extraction rule automatically generate and/or to manually enter an extraction rule. The user may be enabled to manually edit a previously provided extraction rule, which may result in real time display of updated extracted values. The extraction rule may be utilized to extract values from each of a plurality of records, including event records of unstructured machine data. Statistics may be determined for each unique extracted value, and may be displayed to the user in real time. The user interface may also enable the user to select at least one unique extracted value to display those event records that include an extracted value that matches the selected value.

CROSS-REFERENCE TO RELATED APPLICATION(S)

The present application is a Continuation of U.S. application Ser. No.13/748,360 (Atty. Docket No. SPLK 1011-1) filed Jan. 23, 2013, entitled“REAL TIME DISPLAY OF STATISTICS AND VALUES FOR SELECTED REGULAREXPRESSIONS,” which is incorporated herein by reference in theirentirety.

The present application is also related to the contemporaneously filedU.S. Nonprovisional application, which is a Continuation of U.S.application Ser. No. 13/748,360 (Atty. Docket No. SPLK 1011-1) filedJan. 23, 2013, entitled “COUNT BASED REAL TIME DISPLAY OF STATISTICS ANDVALUES FOR SELECTED REGULAR EXPRESSIONS” (Atty. Docket No. SPLK 1101-3).

TECHNICAL FIELD

The present invention relates generally to data presentation management,and more particularly, but not exclusively, to providing real timedisplay of statistics and data field values based for selectedextraction rules.

BACKGROUND

The rapid increase in the production and collection of machine-generateddata has created large data sets that are difficult to search and/orotherwise analyze. The machine data can include sequences of timestamped records that may occur in one or more usually continuousstreams. Further, machine data often represents activity made up ofdiscrete records or events.

Often, search engines may receive data from various data sources,including machine data. In some cases, this data may be analyzed orprocessed in a variety of ways. However, prior to such processing, fieldvalues may need to be extracted from the received data. Sometimes thereceived data may be unstructured, which may make it difficult forsystems to efficiently analyze the received data to determine what datamay be of interest and/or how to generate a field value extraction rule.This may be especially true where the datasets are considered extremelylarge, such as terabytes or greater. Such large unstructured datasetsmay make it difficult and time consuming to analyze the data so as to beable to perform various actions on the data. For example, determiningextraction rules, modification rules, or the like on such large datasetsthat are correct and effective may be difficult and time consuming.Improper and/or ineffective rules may result in improper value from thereceived data and/or omit significant values. Thus, it is with respectto these considerations and others that the present invention has beenmade.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments are described with referenceto the following drawings. In the drawings, like reference numeralsrefer to like parts throughout the various figures unless otherwisespecified.

For a better understanding, reference will be made to the followingDetailed Description, which is to be read in association with theaccompanying drawings, wherein:

FIG. 1 illustrates a system environment in which various embodiments maybe implemented;

FIG. 2A shows a rack of blade servers that may be included in variousembodiments;

FIG. 2B illustrates an embodiment of a blade server that may be includedin a rack of blade servers such as that shown in FIG. 2A;

FIG. 3 shows a client device that may be included in variousembodiments;

FIG. 4 illustrates a network device that may be included in variousembodiments;

FIG. 5 illustrates a logical flow diagram generally showing oneembodiment of an overview process for enabling real time display ofextracted values and corresponding statistics for event records;

FIG. 6 illustrates a logical flow diagram generally showing oneembodiment of a process for enabling real time display of event recordsand extracted values based on manual editing of a data field extractionrule;

FIG. 7 illustrates a logical flow diagram generally showing oneembodiment of a process for enabling the filtering of event recordsbased on a selected extracted value;

FIG. 8A illustrates non-exhaustive examples of a use case of embodimentsof a graphical user interface that may be employed to enable a user tocreate extraction rule and to obtain real time display of extractedvalues;

FIG. 8B illustrates non-exhaustive examples of a use case of embodimentsof a graphical user interface that may be employed to enable a user tocreate extraction rule and to obtain real time display of extractedvalues;

FIG. 8C illustrates non-exhaustive examples of a use case of embodimentsof a graphical user interface that may be employed to enable a user tocreate extraction rule and to obtain real time display of extractedvalues;

FIG. 9A illustrates a use case example of a real time display of anevent record based on manual editing of an extraction rule; and

FIG. 9B illustrates a use case example of a real time display of anevent record based on manual editing of an extraction rule.

DETAILED DESCRIPTION

Various embodiments now will be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, specific embodiments by which theinvention may be practiced. The embodiments may, however, be embodied inmany different forms and should not be construed as limited to theembodiments set forth herein; rather, these embodiments are provided sothat this disclosure will be thorough and complete, and will fullyconvey the scope of the embodiments to those skilled in the art. Amongother things, the various embodiments may be methods, systems, media, ordevices. Accordingly, the various embodiments may take the form of anentirely hardware embodiment, an entirely software embodiment, or anembodiment combining software and hardware aspects. The followingdetailed description is, therefore, not to be taken in a limiting sense.

Throughout the specification and claims, the following terms take themeanings explicitly associated herein, unless the context clearlydictates otherwise. The phrase “in one embodiment” as used herein doesnot necessarily refer to the same embodiment, though it may.Furthermore, the phrase “in another embodiment” as used herein does notnecessarily refer to a different embodiment, although it may. Thus, asdescribed below, various embodiments may be readily combined, withoutdeparting from the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or”operator, and is equivalent to the term “and/or,” unless the contextclearly dictates otherwise. The term “based on” is not exclusive andallows for being based on additional factors not described, unless thecontext clearly dictates otherwise. In addition, throughout thespecification, the meaning of “a,” “an,” and “the” include pluralreferences. The meaning of “in” includes “in” and “on.”

For example embodiments, the following terms are also used hereinaccording to the corresponding meaning, unless the context clearlydictates otherwise.

The term “machine data” as used herein may include data generated bymachines, including, but not limited to, server logs or other types ofevent data and/or records. In at least one of various embodiments,machine data streams may be time stamped to create time stamped events.For example, information processing environments, such as, firewalls,routers, web servers, application servers and databases may generatestreams of time series data in the form of events. In some cases, eventsmay be generated hundreds or thousands of times per second. In someembodiments, the machine data may be unstructured data, structured data,and/or a combination thereof. Unstructured data may refer to data thatdoes not include at least one predefined field.

The term “extraction rule” and/or “data field extraction rule” may referto instructions that may be applied to identify and extract field valuesfrom data, such as event records. In some embodiments, extraction rulemay define a field within event records from which to extract a value.In at least one of various embodiments, the extraction rules may includeregular expressions. The data from which extraction rules may be appliedmay include structured and/or unstructured machine data, or other typeof data.

As used herein, the term “event record” may refer to computing data thatis collected about an event for a computing system, including, forexample, an action, characteristic, condition (or state) of thecomputing system. For example, such events may be about a computingsystem's performance, actions taken by the computing system, or thelike. Event records may be obtained from various computing log filesgenerated by the computer's operating system, and/or other monitoringapplication. However, event records are not restricted by a file formator structure from which the event data is obtained. In variousembodiments, event records may include structured and/or unstructuredmachine data, and/or a combination thereof.

The term “regular expression” as used herein may refer to a sequence ofconstants and operators arranged into expressions for matching a set ofstrings. A regular expression is often defined as a pattern matchinglanguage which can be employed to identify character strings, forexample, to select specific strings from a set of character strings.More particularly, regular expressions are often defined as acontext-independent syntax that can represent a wide variety ofcharacter sets and character set orderings. In operation, regularexpressions can be employed to search data based upon a predefinedpattern or set of patterns. As such, this pattern matching languageemploys a specific syntax by which particular characters or strings areselected from a body of text. Although simple examples of regularexpressions can be easily understood, oftentimes, the syntax of regularexpressions are so complex that even the most experienced programmershave difficulty in understanding them. Regular expressions may beconstructed using a variety of computer languages and constructs. Inaddition to matching, some regular expression systems offerfunctionality, such as, substitution, grouping, back references, or thelike. Regular expressions and regular expression systems may be adaptedto work with non-string data providing matching facilities for binarydata.

The following briefly describes embodiments in order to provide a basicunderstanding of some aspects of the invention. This brief descriptionis not intended as an extensive overview. It is not intended to identifykey or critical elements, or to delineate or otherwise narrow the scope.Its purpose is merely to present some concepts in a simplified form as aprelude to the more detailed description that is presented later.

Briefly stated, various embodiments are directed towards real timedisplay of event records and extracted values based on at least oneextraction rule. In at least one embodiment, a user interface may beemployed to enable a user to have an extraction rule automaticallygenerate and/or to manually enter an extraction rule. In at least oneembodiment, the extraction rule may include a regular expression. Inother embodiments, the user may be enabled to manually edit a previouslyprovided extraction rule, which may result in real time display ofupdated extracted values as the user is editing the extraction rule. Theextraction rule may be utilized to extract values from each of aplurality of records, including event records of unstructured machinedata. In some other embodiments, statistics, such as a percentage may bedetermined for each unique extracted value, and may be displayed to theuser in real time. Real time display of the extracted values,statistics, and event records may occur as an extraction rule is beingmanipulated and/or edited by the user. In some embodiments, the userinterface may enable the user to select at least one unique extractedvalue to display those event records that include an extracted valuethat matches the selected value.

Illustrative Operating Environment

FIG. 1 shows components of an environment in which various embodimentsmay be practiced. Not all of the components may be required to practicethe various embodiments, and variations in the arrangement and type ofthe components may be made without departing from the spirit or scope ofthe various embodiments.

In at least one embodiment, cloud network 102 enables one or morenetwork services for a user based on the operation of correspondingarrangements 104 and 106 of virtually any type of networked computingdevice. As shown, the networked computing devices may include extractionrule server device 112, event records server device 114, enclosure ofblade servers 110, enclosure of server computers 116, super computernetwork device 118, and the like. Although not shown, one or more clientdevices may be included in cloud network 102 in one or more arrangementsto provide one or more network services to a user. Also, thesearrangements of networked computing devices may or may not be mutuallyexclusive of each other.

Additionally, the user may employ a plurality of virtually any type ofwired or wireless networked computing devices to communicate with cloudnetwork 102 and access at least one of the network services enabled byone or more of arrangements 104 and 106. These networked computingdevices may include tablet client device 122, handheld client device124, wearable client device 126, desktop client device 120, and thelike. Although not shown, in various embodiments, the user may alsoemploy notebook computers, desktop computers, microprocessor-based orprogrammable consumer electronics, network appliances, mobiletelephones, smart telephones, pagers, radio frequency (RF) devices,infrared (IR) devices, Personal Digital Assistants (PDAs), televisions,integrated devices combining at least one of the preceding devices, andthe like.

One embodiment of a client device is described in more detail below inconjunction with FIG. 3. Generally, client devices may include virtuallyany substantially portable networked computing device capable ofcommunicating over a wired, wireless, or some combination of wired andwireless network.

In various embodiments, network 102 may employ virtually any form ofcommunication technology and topology. For example, network 102 caninclude local area networks Personal Area Networks (PANs), (LANs),Campus Area Networks (CANs), Metropolitan Area Networks (MANs) Wide AreaNetworks (WANs), direct communication connections, and the like, or anycombination thereof. On an interconnected set of LANs, including thosebased on differing architectures and protocols, a router acts as a linkbetween LANs, enabling messages to be sent from one to another. Inaddition, communication links within networks may include virtually anytype of link, e.g., twisted wire pair lines, optical fibers, open airlasers or coaxial cable, plain old telephone service (POTS), waveguides, acoustic, full or fractional dedicated digital communicationlines including T1, T2, T3, and T4, and/or other carrier and other wiredmedia and wireless media. These carrier mechanisms may includeE-carriers, Integrated Services Digital Networks (ISDNs), universalserial bus (USB) ports, Firewire ports, Thunderbolt ports, DigitalSubscriber Lines (DSLs), wireless links including satellite links, orother communications links known to those skilled in the art. Moreover,these communication links may further employ any of a variety of digitalsignaling technologies, including without limit, for example, DS-0,DS-1, DS-2, DS-3, DS-4, OC-3, OC-12, OC-48, or the like. Furthermore,remotely located computing devices could be remotely connected tonetworks via a modem and a temporary communication link. In essence,network 102 may include virtually any communication technology by whichinformation may travel between computing devices. Additionally, in thevarious embodiments, the communicated information may include virtuallyany kind of information including, but not limited to processor-readableinstructions, data structures, program modules, applications, raw data,control data, archived data, video data, voice data, image data, textdata, and the like.

Network 102 may be partially or entirely embodied by one or morewireless networks. A wireless network may include any of a variety ofwireless sub-networks that may further overlay stand-alone ad-hocnetworks, and the like. Such sub-networks may include mesh networks,Wireless LAN (WLAN) networks, Wireless Router (WR) mesh, cellularnetworks, pico networks, PANs, Open Air Laser networks, Microwavenetworks, and the like. Network 102 may further include an autonomoussystem of intermediate network devices such as terminals, gateways,routers, switches, firewalls, load balancers, and the like, which arecoupled to wired and/or wireless communication links. These autonomousdevices may be operable to move freely and randomly and organizethemselves arbitrarily, such that the topology of network 102 may changerapidly.

Network 102 may further employ a plurality of wired and wireless accesstechnologies, e.g., 2nd (2G), 3rd (3G), 4th (4G), 5^(th) (5G) generationwireless access technologies, and the like, for mobile devices. Thesewired and wireless access technologies may also include Global Systemfor Mobile communication (GSM), General Packet Radio Services (GPRS),Enhanced Data GSM Environment (EDGE), Code Division Multiple Access(CDMA), Wideband Code Division Multiple Access (WCDMA), Long TermEvolution Advanced (LTE), Universal Mobile Telecommunications System(UMTS), Orthogonal frequency-division multiplexing (OFDM), Wideband CodeDivision Multiple Access (W-CDMA), Code Division Multiple Access 2000(CDMA2000), Evolution-Data Optimized (EV-DO), High-Speed Downlink PacketAccess (HSDPA), IEEE 802.16 Worldwide Interoperability for MicrowaveAccess (WiMax), ultra wide band (UWB), user datagram protocol (UDP),transmission control protocol/Internet protocol (TCP/IP), any portion ofthe Open Systems Interconnection (OSI) model protocols, Short MessageService (SMS), Multimedia Messaging Service (MMS), Web Access Protocol(WAP), Session Initiation Protocol/Real-time Transport Protocol(SIP/RTP), or any of a variety of other wireless or wired communicationprotocols. In one non-limiting example, network 102 may enable a mobiledevice to wirelessly access a network service through a combination ofseveral radio network access technologies such as GSM, EDGE, SMS, HSDPA,and the like.

One embodiment of extraction rule server device 112 is described in moredetail below in conjunction with FIG. 4. Briefly, however, extractionrule server device 112 includes virtually any network device capable ofgenerating and/or managing extraction rules. In some embodiments,extraction rule server device 112 may automatically generate extractionrules. Devices that may be arranged to operate as extraction rule serverdevice 112 include various network devices, including, but not limitedto personal computers, desktop computers, multiprocessor systems,microprocessor-based or programmable consumer electronics, network PCs,server devices, network appliances, and the like.

Although FIG. 1 illustrates extraction rule server device 112 as asingle computing device, the invention is not so limited. For example,one or more functions of the extraction rule server device 112 may bedistributed across one or more distinct network devices. Moreover,extraction rule server device 112 is not limited to a particularconfiguration. Thus, in one embodiment, extraction rule server device112 may contain a plurality of network devices. In another embodiment,extraction rule server device 112 may contain a plurality of networkdevices that operate using a master/slave approach, where one of theplurality of network devices of extraction rule server device 112operates to manage and/or otherwise coordinate operations of the othernetwork devices. In other embodiments, the extraction rule server device112 may operate as a plurality of network devices within a clusterarchitecture, a peer-to-peer architecture, and/or even within a cloudarchitecture. Thus, the invention is not to be construed as beinglimited to a single environment, and other configurations, andarchitectures are also envisaged.

One embodiment of event records server device 114 is described in moredetail below in conjunction with FIG. 4. Briefly, however, event recordsserver device 114 includes virtually any network device capable ofcollecting and/or maintaining event records. In some embodiments, eventrecords server device 114 may be in communication with extraction ruleserver device 112 to enable the use of extraction rules on eventrecords. Devices that may be arranged to operate as event records serverdevice 114 include various network devices, including, but not limitedto personal computers, desktop computers, multiprocessor systems,microprocessor-based or programmable consumer electronics, network PCs,server devices, network appliances, and the like.

Although FIG. 1 illustrates event records server device 114 as a singlecomputing device, the invention is not so limited. For example, one ormore functions of the event records server device 114 may be distributedacross one or more distinct network devices. Moreover, event recordsserver device 114 is not limited to a particular configuration. Thus, inone embodiment, event records server device 114 may contain a pluralityof network devices. In another embodiment, event records server device114 may contain a plurality of network devices that operate using amaster/slave approach, where one of the plurality of network devices ofevent records server device 114 operates to manage and/or otherwisecoordinate operations of the other network devices. In otherembodiments, the event records server device 114 may operate as aplurality of network devices within a cluster architecture, apeer-to-peer architecture, and/or even within a cloud architecture.Thus, the invention is not to be construed as being limited to a singleenvironment, and other configurations, and architectures are alsoenvisaged.

Enclosure of Blade Servers

FIG. 2A shows one embodiment of an enclosure of blade servers 200, whichare also illustrated in FIG. 1. Enclosure of blade servers 200 mayinclude many more or fewer components than those shown in FIG. 2A.However, the components shown are sufficient to disclose an illustrativeembodiment. Generally, a blade server is a stripped down servercomputing device with a modular design optimized to minimize the use ofphysical space and energy. A blade enclosure can include several bladeservers and provide each with power, cooling, network interfaces,input/output interfaces, and resource management. Although not shown, anenclosure of server computers typically includes several computers thatmerely require a network connection and a power cord connection tooperate. Each server computer often includes redundant components forpower and interfaces.

As shown in the FIG., enclosure 200 contains power supply 204, andinput/output interface 206, rack logic 208, several blade servers 210,212, 214, and 216, and backplane 202. Power supply 204 provides power toeach component and blade server within the enclosure. The input/outputinterface 206 provides internal and external communication forcomponents and blade servers within the enclosure. Backplane 208 canenable passive and active communication of power, logic, input signals,and output signals for each blade server.

Illustrative Blade Server

FIG. 2B illustrates an illustrative embodiment of blade server 250,which may include many more or fewer components than those shown. Asshown in FIG. 2A, a plurality of blade servers may be included in oneenclosure that shares resources provided by the enclosure to reducesize, power, and cost.

Blade server 250 may include processor 252 which communicates withmemory 256 via bus 254. Blade server 250 may also include input/outputinterface 290, processor-readable stationary storage device 292, andprocessor-readable removable storage device 294. Input/output interface290 can enable blade server 250 to communicate with other blade servers,client devices, network devices, and the like. Interface 290 may providewireless and/or wired communication links for blade server.Processor-readable stationary storage device 292 may include devicessuch as an electromagnetic storage device (hard disk), solid state harddisk (SSD), hybrid of both an SSD and a hard disk, and the like. Also,processor-readable removable storage device 294 enables processor 252 toread non-transitive storage media for storing and accessingprocessor-readable instructions, modules, data structures, and otherforms of data. The non-transitive storage media may include Flashdrives, tape media, floppy media, and the like.

Memory 256 may include Random Access Memory (RAM), Read-Only Memory(ROM), hybrid of RAM and ROM, and the like. As shown, memory 256includes operating system 258 and basic input/output system (BIOS) 260for enabling the operation of blade server 250. In various embodiments,a general-purpose operating system may be employed such as a version ofUNIX, or LINUX™, or a specialized server operating system such asMicrosoft's Windows Server™ and Apple Computer's iOS Server™.

Memory 256 may further include one or more data storage 270, which canbe utilized by blade server 250 to store, among other things,applications 280 and/or other data. Data stores 270 may include programcode, data, algorithms, and the like, for use by processor 252 toexecute and perform actions. In one embodiment, at least some of datastore 270 might also be stored on another component of blade server 250,including, but not limited to, processor-readable removable storagedevice 294, processor-readable stationary storage device 292, or anyother processor-readable storage device (not shown). Data storage 270may include, for example, event records 272 and extraction rules 274.

Applications 280 may include processor executable instructions which,when executed by blade server 250, transmit, receive, and/or otherwiseprocess messages, audio, video, and enable communication with othernetworked computing devices. Examples of application programs includedatabase servers, file servers, calendars, transcoders, and so forth.Applications 280 may include, for example, extraction rule application282.

Human interface components (not pictured), may be remotely associatedwith blade server 250, which can enable remote input to and/or outputfrom blade server 250. For example, information to a display or from akeyboard can be routed through the input/output interface 290 toappropriate peripheral human interface components that are remotelylocated. Examples of peripheral human interface components include, butare not limited to, an audio interface, a display, keypad, pointingdevice, touch interface, and the like.

Illustrative Client Device

FIG. 3 shows one embodiment of client device 300 that may include manymore or less components than those shown. Client device 300 mayrepresent, for example, at least one embodiment of client devices shownin FIG. 1.

Client device 300 may include processor 302 in communication with memory304 via bus 328. Client device 300 may also include power supply 330,network interface 332, audio interface 356, display 350, keypad 352,illuminator 354, video interface 342, input/output interface 338, hapticinterface 364, global positioning systems (GPS) receiver 358, open airgesture interface 360, temperature interface 362, camera(s) 340,projector 346, pointing device interface 366, processor-readablestationary storage device 334, and processor-readable removable storagedevice 336. Client device 300 may optionally communicate with a basestation (not shown), or directly with another computing device. And inone embodiment, although not shown, a gyroscope may be employed withinclient device 300 to measuring and/or maintaining an orientation ofclient device 300.

Power supply 330 may provide power to client device 300. A rechargeableor non-rechargeable battery may be used to provide power. The power mayalso be provided by an external power source, such as an AC adapter or apowered docking cradle that supplements and/or recharges the battery.

Network interface 332 includes circuitry for coupling client device 300to one or more networks, and is constructed for use with one or morecommunication protocols and technologies including, but not limited to,protocols and technologies that implement any portion of the OSI modelfor mobile communication (GSM), CDMA, time division multiple access(TDMA), UDP, TCP/IP, SMS, MMS, GPRS, WAP, UWB, WiMax, SIP/RTP, GPRS,EDGE, WCDMA, LTE, UMTS, OFDM, CDMA2000, EV-DO, HSDPA, or any of avariety of other wireless communication protocols. Network interface 332is sometimes known as a transceiver, transceiving device, or networkinterface card (NIC).

Audio interface 356 may be arranged to produce and receive audio signalssuch as the sound of a human voice. For example, audio interface 356 maybe coupled to a speaker and microphone (not shown) to enabletelecommunication with others and/or generate an audio acknowledgementfor some action. A microphone in audio interface 356 can also be usedfor input to or control of client device 300, e.g., using voicerecognition, detecting touch based on sound, and the like.

Display 350 may be a liquid crystal display (LCD), gas plasma,electronic ink, light emitting diode (LED), Organic LED (OLED) or anyother type of light reflective or light transmissive display that can beused with a computing device. Display 350 may also include a touchinterface 344 arranged to receive input from an object such as a stylusor a digit from a human hand, and may use resistive, capacitive, surfaceacoustic wave (SAW), infrared, radar, or other technologies to sensetouch and/or gestures.

Projector 346 may be a remote handheld projector or an integratedprojector that is capable of projecting an image on a remote wall or anyother reflective object such as a remote screen.

Video interface 342 may be arranged to capture video images, such as astill photo, a video segment, an infrared video, or the like. Forexample, video interface 342 may be coupled to a digital video camera, aweb-camera, or the like. Video interface 342 may comprise a lens, animage sensor, and other electronics. Image sensors may include acomplementary metal-oxide-semiconductor (CMOS) integrated circuit,charge-coupled device (CCD), or any other integrated circuit for sensinglight.

Keypad 352 may comprise any input device arranged to receive input froma user. For example, keypad 352 may include a push button numeric dial,or a keyboard. Keypad 352 may also include command buttons that areassociated with selecting and sending images.

Illuminator 354 may provide a status indication and/or provide light.Illuminator 354 may remain active for specific periods of time or inresponse to events. For example, when illuminator 354 is active, it maybacklight the buttons on keypad 352 and stay on while the client deviceis powered. Also, illuminator 354 may backlight these buttons in variouspatterns when particular actions are performed, such as dialing anotherclient device. Illuminator 354 may also cause light sources positionedwithin a transparent or translucent case of the client device toilluminate in response to actions.

Client device 300 may also comprise input/output interface 338 forcommunicating with external peripheral devices or other computingdevices such as other client devices and network devices. The peripheraldevices may include an audio headset, display screen glasses, remotespeaker system, remote speaker and microphone system, and the like.Input/output interface 338 can utilize one or more technologies, such asUniversal Serial Bus (USB), Infrared, WiFi, WiMax, Bluetooth™, and thelike.

Haptic interface 364 may be arranged to provide tactile feedback to auser of the client device. For example, the haptic interface 364 may beemployed to vibrate client device 300 in a particular way when anotheruser of a computing device is calling. Temperature interface 362 may beused to provide a temperature measurement input and/or a temperaturechanging output to a user of client device 300. Open air gestureinterface 360 may sense physical gestures of a user of client device300, for example, by using single or stereo video cameras, radar, agyroscopic sensor inside a device held or worn by the user, or the like.Camera 340 may be used to track physical eye movements of a user ofclient device 300.

GPS transceiver 358 can determine the physical coordinates of clientdevice 300 on the surface of the Earth, which typically outputs alocation as latitude and longitude values. GPS transceiver 358 can alsoemploy other geo-positioning mechanisms, including, but not limited to,triangulation, assisted GPS (AGPS), Enhanced Observed Time Difference(E-OTD), Cell Identifier (CI), Service Area Identifier (SAI), EnhancedTiming Advance (ETA), Base Station Subsystem (BSS), or the like, tofurther determine the physical location of client device 300 on thesurface of the Earth. It is understood that under different conditions,GPS transceiver 358 can determine a physical location for client device300. In at least one embodiment, however, client device 300 may, throughother components, provide other information that may be employed todetermine a physical location of the device, including for example, aMedia Access Control (MAC) address, IP address, and the like.

Human interface components can be peripheral devices that are physicallyseparate from client device 300, allowing for remote input and/or outputto client device 300. For example, information routed as described herethrough human interface components such as display 350 or keyboard 352can instead be routed through network interface 332 to appropriate humaninterface components located remotely. Examples of human interfaceperipheral components that may be remote include, but are not limitedto, audio devices, pointing devices, keypads, displays, cameras,projectors, and the like. These peripheral components may communicateover a Pico Network such as Bluetooth™, Zigbee™ and the like. Onenon-limiting example of a client device with such peripheral humaninterface components is a wearable computing device, which might includea remote pico projector along with one or more cameras that remotelycommunicate with a separately located client device to sense a user'sgestures toward portions of an image projected by the pico projectoronto a reflected surface such as a wall or the user's hand.

A client device may include a browser application that is configured toreceive and to send web pages, web-based messages, graphics, text,multimedia, and the like. The client device's browser application mayemploy virtually any programming language, including a wirelessapplication protocol messages (WAP), and the like. In at least oneembodiment, the browser application is enabled to employ Handheld DeviceMarkup Language (HDML), Wireless Markup Language (WML), WMLScript,JavaScript, Standard Generalized Markup Language (SGML), HyperTextMarkup Language (HTML), eXtensible Markup Language (XML), HTML5, and thelike.

Memory 304 may include RAM, ROM, and/or other types of memory. Memory304 illustrates an example of computer-readable storage media (devices)for storage of information such as computer-readable instructions, datastructures, program modules or other data. Memory 304 may store BIOS 308for controlling low-level operation of client device 300. The memory mayalso store operating system 306 for controlling the operation of clientdevice 300. It will be appreciated that this component may include ageneral-purpose operating system such as a version of UNIX, or LINUX™,or a specialized mobile computer communication operating system such asWindows Phone™, or the Symbian® operating system. The operating systemmay include, or interface with a Java virtual machine module thatenables control of hardware components and/or operating systemoperations via Java application programs.

Memory 304 may further include one or more data storage 310, which canbe utilized by client device 300 to store, among other things,applications 320 and/or other data. For example, data storage 310 mayalso be employed to store information that describes variouscapabilities of client device 300. The information may then be providedto another device based on any of a variety of events, including beingsent as part of a header during a communication, sent upon request, orthe like. Data storage 310 may also be employed to store socialnetworking information including address books, buddy lists, aliases,user profile information, or the like. Data storage 310 may furtherinclude program code, data, algorithms, and the like, for use by aprocessor, such as processor 302 to execute and perform actions. In oneembodiment, at least some of data storage 310 might also be stored onanother component of client device 300, including, but not limited to,non-transitory processor-readable removable storage device 336,processor-readable stationary storage device 334, or even external tothe client device.

Applications 320 may include computer executable instructions which,when executed by client device 300, transmit, receive, and/or otherwiseprocess instructions and data. Applications 320 may include, forexample, extraction rule application 322. Other examples of applicationprograms include calendars, search programs, email client applications,IM applications, SMS applications, Voice Over Internet Protocol (VOIP)applications, contact managers, task managers, transcoders, databaseprograms, word processing programs, security applications, spreadsheetprograms, games, search programs, and so forth.

Extraction rule application 322 may be configured to enable creation ofextraction rules and to display results of the extraction rules to auser. In at least one embodiment, extraction rule application 322 mayinteract with and/or employed through a web browser. In someembodiments, embodiments, extraction rule application 322 may enable auser to input and/or edit one or more extraction rules. In otherembodiments, extraction rule application 322 may display a plurality ofevent records to a user, values extracted from the event records usingthe extraction rule, statistics about the extracted values, or the like.In any event, extraction rule application 322 may employ processes, orparts of processes, similar to those described in conjunction with FIGS.5-7, to perform at least some of its actions.

Illustrative Network Device

FIG. 4 shows one embodiment of network device 400 that may be includedin a system implementing the invention. Network device 400 may includemany more or less components than those shown in FIG. 4. However, thecomponents shown are sufficient to disclose an illustrative embodimentfor practicing the present invention. Network device 400 may represent,for example, one embodiment of at least one of network device 112, 114,or 120 of FIG. 1.

As shown in the FIG., network device 400 may include a processor 402 incommunication with a memory 404 via a bus 428. Network device 400 mayalso include a power supply 430, network interface 432, audio interface456, display 450, keyboard 452, input/output interface 438,processor-readable stationary storage device 434, processor-readableremovable storage device 436, and pointing device interface 458. Powersupply 430 provides power to network device 400.

Network interface 432 may include circuitry for coupling network device400 to one or more networks, and is constructed for use with one or morecommunication protocols and technologies including, but not limited to,protocols and technologies that implement any portion of the OpenSystems Interconnection model (OSI model), GSM, CDMA, time divisionmultiple access (TDMA), UDP, TCP/IP, SMS, MMS, GPRS, WAP, UWB, WiMax,SIP/RTP, or any of a variety of other wired and wireless communicationprotocols. Network interface 432 is sometimes known as a transceiver,transceiving device, or network interface card (NIC). Network device 400may optionally communicate with a base station (not shown), or directlywith another computing device.

Audio interface 456 is arranged to produce and receive audio signalssuch as the sound of a human voice. For example, audio interface 456 maybe coupled to a speaker and microphone (not shown) to enabletelecommunication with others and/or generate an audio acknowledgementfor some action. A microphone in audio interface 456 can also be usedfor input to or control of network device 400, for example, using voicerecognition.

Display 450 may be a liquid crystal display (LCD), gas plasma,electronic ink, light emitting diode (LED), Organic LED (OLED) or anyother type of light reflective or light transmissive display that can beused with a computing device. Display 450 may be a handheld projector orpico projector capable of projecting an image on a wall or other object.

Network device 400 also may also comprise input/output interface 438 forcommunicating with external devices not shown in FIG. 4. Input/outputinterface 438 can utilize one or more wired or wireless communicationtechnologies, such as USB™, Firewire™, WiFi, WiMax, Thunderbolt™,Infrared, Bluetooth™, Zigbee™, serial port, parallel port, and the like.

Human interface components can be physically separate from networkdevice 400, allowing for remote input and/or output to network device400. For example, information routed as described here through humaninterface components such as display 450 or keyboard 452 can instead berouted through the network interface 432 to appropriate human interfacecomponents located elsewhere on the network. Human interface componentscan include any component that allows the computer to take input from,or send output to, a human user of a computer.

Memory 404 may include RAM, ROM, and/or other types of memory. Memory404 illustrates an example of computer-readable storage media (devices)for storage of information such as computer-readable instructions, datastructures, program modules or other data. Memory 404 may store BIOS 408for controlling low-level operation of network device 400. The memorymay also store operating system 406 for controlling the operation ofnetwork device 400. It will be appreciated that this component mayinclude a general-purpose operating system such as a version of UNIX, orLINUX™, or a specialized operating system such as MicrosoftCorporation's Windows® operating system, or the Apple Corporation's iOS®operating system. The operating system may include, or interface with aJava virtual machine module that enables control of hardware componentsand/or operating system operations via Java application programs.

Memory 404 may further include one or more data storage 410, which canbe utilized by network device 400 to store, among other things,applications 420 and/or other data. For example, data storage 410 mayalso be employed to store information that describes variouscapabilities of network device 400. The information may then be providedto another device based on any of a variety of events, including beingsent as part of a header during a communication, sent upon request, orthe like. Data storage 410 may also be employed to store socialnetworking information including address books, buddy lists, aliases,user profile information, or the like. Data stores 410 may furtherinclude program code, data, algorithms, and the like, for use by aprocessor, such as processor 402 to execute and perform actions. In oneembodiment, at least some of data store 410 might also be stored onanother component of network device 400, including, but not limited to,non-transitory media inside processor-readable removable storage device436, processor-readable stationary storage device 434, or any othercomputer-readable storage device within network device 400, or evenexternal to network device 400.

Data storage 410 may include, for example, event records 412 andextraction rules 416. In some embodiments, event records 412 may storedata, including a plurality of event records. In at least one of variousembodiments, event records 412 may be stored by event records serverdevice 114 of FIG. 1. Extraction rules 416 may include one or moreextractions rules. These extraction rules may be automatically createdbased on a user selection of text, input by a user, and/or otherwiseprovided to the system. In at least one embodiment, extraction rules 416may be stored and/or otherwise processed by extraction rule serverdevice 112 of FIG. 1.

Applications 420 may include computer executable instructions which,when executed by network device 400, transmit, receive, and/or otherwiseprocess messages (e.g., SMS, MMS, Instant Message (IM), email, and/orother messages), audio, video, and enable telecommunication with anotheruser of another client device. Other examples of application programsinclude calendars, search programs, email client applications, IMapplications, SMS applications, Voice Over Internet Protocol (VOIP)applications, contact managers, task managers, transcoders, databaseprograms, word processing programs, security applications, spreadsheetprograms, games, search programs, and so forth. Applications 420 mayinclude, for example, extraction rule application 422.

Extraction rule application 422 may be configured to enable creation ofextraction rules and to display results of the extraction rules to auser. In at least one embodiment, extraction rule application 422 mayinteract with a client device for enabling a user to input and/or editone or more extraction rules. In other embodiments, extraction ruleapplication 422 may enable a client device to display a plurality ofevent records to a user, values extracted from the event records usingthe extraction rule, statistics about the extracted values, or the like.In at least one embodiment, extraction rule application 422 may interactwith event records 412 and/or extraction rules 416 to access and/orstore event records and/or extraction rules, respectively. In someembodiments, extraction rule application 422 may be employed byextraction rule server device 112 of FIG. 1. In any event, extractionrule application 422 may employ processes, or parts of processes,similar to those described in conjunction with FIGS. 5 through 7, toperform at least some of its actions.

General Operation

The operation of certain aspects of the invention will now be describedwith respect to FIGS. 5 through 7. FIG. 5 illustrates a logical flowdiagram generally showing one embodiment of an overview process forenabling real time display of extracted values and correspondingstatistics for event records. In some embodiments, process 500 of FIG. 5may be implemented by and/or executed on a single network device, suchas network device 400 of FIG. 4. In other embodiments, process 500 orportions of process 500 of FIG. 5 may be implemented by and/or executedon a plurality of network devices, such as network device 400 of FIG. 4.In yet other embodiments, process 500 or portions of process 500 of FIG.5 may be implemented by and/or executed on one or more blade servers,such as blade server 250 of FIG. 2B. However, embodiments are not solimited and various combinations of network devices, blade servers, orthe like may be utilized.

Process 500 begins, after a start block, at block 502, where a pluralityof event records may be provided. In some embodiments, the event recordsmay be provided by a plurality of different computing devices, such asclient devices. In at least one embodiment, the plurality of eventrecords may be a sample subset of a larger dataset of event recordsdataset. In some embodiments, the larger dataset of event records may beassociated with one or more users and/or clients. As described above,the event records may be structured data and/or unstructured data.Additionally, the event records may include machine data.

Process 500 proceeds next to block 504, where a data field extractionrule may be provided. In various embodiments, the extraction rule may beautomatically generated, manually input by a user, previouslyprovided/created, provided by another system, or the like, or anycombination thereof. The extraction rule may define a field within theplurality of event records from which to extract data (e.g., a fieldvalue). Accordingly, in some embodiments, the extraction rule may definea field within the event records independent of a predetermined and/orpredefined structure of the event records.

In at least one embodiment, automatic generation of an extraction rulemay be based on a value selected from an event record. In someembodiments, a graphical user interface (GUI) may be employed to enablea user to select desired text of an event record. From the selectedtext, pattern recognition algorithms may be employed to automaticallygenerate the extraction rule. In at least one embodiment, the extractionrule may be a regular expression.

In another embodiment, the GUI may be employed to enable the user tomanually input the extraction rule. In at least one embodiment, the usermay enter a regular expression or other extraction rule into an editableinput text box in the GUI to define a field within the event recordsfrom which to extract data. In yet other embodiments, the user mayutilize the GUI to manually edit extraction rules—either previouslyautomatically generated extraction rules or previous user-enteredextraction rules.

As extraction rules are being generated and/or edited, the GUI maydisplay real time updates of newly extracted values, statistics thatcorrespond to the extracted values, changes to a display of the eventrecords, or the like, or any combination thereof. Various embodiments ofreal time display of field values based on manual editing of extractionrules is described in more detail below in conjunction with FIG. 6.

In some embodiments, the GUI may be employed to enable a user to providea field name for the extraction rule (e.g., the field defined by theextraction rule). In other embodiments, the system may automaticallydetermine a field name for the extraction rule. In at least one suchembodiment, the system may employ the extraction rule to extract a valuefrom one or more event records. The field name may be determined basedon this value, such as, for example, a datatype of the extracted value(e.g., an integer), a format of the extracted value (e.g., a phonenumber, URL, time/date format, or the like), or the like. In variousembodiments, the extraction rule may be automatically generated,manually input by a user, or the like, or any combination thereof.

In any event, process 500 continues next at block 506, where a value maybe extracted from each of the plurality of event records based on theextraction rule. In at least one of various embodiments, the extractionrule may be applied to each of the plurality of event records todetermine what data to extract from each event record. The extracteddata from a given event record may be the particular value for thatevent record for the field defined by the extraction rule. For example,if an extraction rule defines a field as the characters between a firstset of single brackets, then the value for the event record “Dec 1710:35:38 ronnie nslcd[23629]: [40f750] passwd entry uid” may be “23629”.

Proceeding to block 508, at least one statistic may be determined foreach unique extracted value. In at least one embodiment, a uniqueextracted value may be an extracted value that is different than anotherextracted value, regardless and/or independent of a number of instancesthat a value is extracted from the plurality of event records. Forexample, assume the extracted values from a six event records includes[“Bob”, “Bob”, “Ralph”, “Bob”, “John”, “Ralph”]. The unique extractedvalues may be “Bob”, “Ralph”, and “John”.

Based on the extracted unique values, statistics may be determined. Inat least one embodiment, a statistic for a unique value may be a totalnumber of times the unique value occurs in the plurality of records. Inanother embodiment, a statistic for a unique value may be a percent of anumber of times the unique value occurs compared to a number of recordsin the plurality of records. In yet another embodiment, a statistic fora unique value may be a percent of a number of times the unique valueoccurs compared to a number of extracted values. This number may bedifferent than a number of records in the plurality of records if theextraction rule does not result in a value being extracted from at leastone event record. For example, assume an extraction rule defines a fieldas the characters between a first set of single brackets. If an eventrecord does not include single brackets, then no value may be extracted.However, embodiments are not limited to these types of statistics andother statistics and/or metrics may also be employed.

Process 500 continues next at block 510, where the GUI may be employedto display the event records based on the extraction rule in real time.In at least one embodiment, the plurality of event records may bedisplayed to the user in virtually any order, such as, most recent tolatest or the like. In at least one embodiment, displaying an eventrecord based on an extraction rule may include emphasizing the fielddefined by the extraction rule (e.g., the extracted value) in the eventrecord. Examples of such emphasizing may include, but are not limitedto, highlighting, underlining, and/or otherwise identifying the valueextracted from the event record. FIG. 8B illustrates one embodiment ofreal time display of event records, where values extracted based on anextraction rule are highlighted. In some other embodiments, a pluralityof extraction rules may be employed for the plurality of event recordsand each corresponding extracted value may be emphasized (in a similaror different manner). In at least one embodiment, the values extractedfrom multiple extractions rules may be distinct and/or separate, and/ormay partially or completely overlap.

In some embodiments, real time display of the event records may includedisplaying the event records based on an extraction rule as theextraction rule is being provided, entered, and/or edited by a user.Accordingly, the GUI may update a display of each event record and anindication of each extracted value in near real time as an extractionrule is edited/generated.

Process 500 proceeds next at block 512, where the GUI may be employed toenable real time display of the unique extracted values and the at leastone corresponding statistic. In some embodiments where multipleextraction rules are employed, a set of unique extracted values andcorresponding statistics may be displayed for each distinct extractionrule.

In some embodiments, real time display of the unique extracted valuesand the at least one corresponding statistic may include displaying theunique extracted values and the at least one corresponding statistic asthe extraction rule is being provided, entered, and/or edited by a user.Accordingly, the GUI may update a display of a list of unique extractedvalues and the at least one corresponding statistic in near real time asan extraction rule is edited/generated.

It should be understood that real time or near real time display ofdata, as used herein, may include a delay created by some processing ofthe data, such as, but not limited to, a time to generate an extractionrule, a time to apply the extraction rule to the plurality of eventrecords, a time to calculate corresponding statistics, and/or the like.

Process 500 may continue at decision block 514, where a determinationmay be made whether a new data field extraction rule has been provided.In at least one embodiment, a new data field extraction rule may beautomatically provided. In another embodiment, a user may edit apreviously provided extraction rule. If a new extraction rule isprovided, process 500 may loop to block 506; otherwise, process 500 mayreturn to a calling process to perform other actions.

FIG. 6 illustrates a logical flow diagram generally showing oneembodiment of a process for enabling real time display of event recordsand extracted values based on manual editing of a data field extractionrule. In some embodiments, process 600 of FIG. 6 may be implemented byand/or executed on a single network device, such as network device 400of FIG. 4. In other embodiments, process 600 or portions of process 600of FIG. 6 may be implemented by and/or executed on a plurality ofnetwork devices, such as network device 400 of FIG. 4. In yet otherembodiments, process 600 or portions of process 600 of FIG. 6 may beimplemented by and/or executed on one or more blade servers, such asblade server 250 of FIG. 2B. However, embodiments are not so limited andvarious combinations of network devices, blade servers, or the like maybe utilized.

Process 600 begins, after a start block, at block 602, where a pluralityof event records may be displayed. In some embodiments, a plurality ofreceived event records may be displayed as a list of records, such as isshown in FIG. 8A. In at least one of various embodiments, block 602 mayemploy embodiments of block 502 of FIG. 5 to receive the plurality ofevent records for display.

Process 600 proceeds to block 604, where an input from a user that editsan extraction rule may be received. In at least one embodiment, a GUImay be employed to enable the user to edit an extraction rule. In onenon-limiting, non-exhaustive example, an extraction rule (e.g., apreviously generated or a newly generated extraction rule) may bedisplayed to the user in an editable text box. The user may then makeedits to the extraction rule by typing in the text box. However,embodiments are not so limited and other graphical interface objects maybe employed to enable a user to manually edit the extraction rule. In atleast one of various embodiments, block 604 may employ embodiments ofblock 504 of FIG. 5 to provide an extraction rule, which may be editedby the user. In other embodiments, the user may manually enter anextraction rule starting from scratch. In some embodiments, theextraction rule may be displayed to the user as source code, which theuser may modify to edit the extraction rule.

Process 600 continues next at block 606, where the displayed eventrecords may be dynamically modified based on the edited extraction rule.In at least one embodiment, as the user edits the extraction rule, anemphasis of the field defined by the edited extraction rule for eachevent record may be modified in real time. For example, a highlightingof text in the event record (i.e., the extracted value) may be modifiedas the extraction rule is being edited that reflects the editedextraction rule. In at least one of various embodiments, block 606 mayemploy embodiments of block 510 of FIG. 5 to enable real time display ofevent records.

Process 600 proceeds next to block 608, where at least one value may beextracted from each of the plurality of event records based on theextraction rule. In at least one of various embodiments, block 608 mayemploy embodiments of block 506 of FIG. 5 to extract values from each ofthe plurality of event records.

Process 600 continues at block 610, where the GUI may be employed todynamically display the extracted values in real time. In at least oneembodiment, as the user is editing the extraction rule, the extractedvalues may change and those changes (e.g., the extracted values based onthe edited extraction rule) may be displayed in real time. In someembodiments, a list of unique extracted values may be displayed. In atleast one of various embodiments, block 610 may employ embodiments ofblock 512 of FIG. 5 to display unique extracted values. In someembodiments, statistics that correspond to the extracted values may alsobe displayed in real time, such as is described at block 508 and 512 ofFIG. 5.

In any event, process 600 proceeds next to decision block 612, where adetermination may be made whether an edit to the data field extractionrule was received. In at least one embodiment, this determination may bebased on input from a user into the GUI, such as editing the extractionrule in an editable text box (e.g., as described at block 604). If theextraction rule was edited, changed, and/or otherwise modified by theuser, then process 600 may loop to block 606; otherwise, process 600 mayreturn to a calling process to perform other actions.

FIG. 7 illustrates a logical flow diagram generally showing oneembodiment of a process for enabling the filtering of event recordsbased on a selected extracted value. In some embodiments, process 700 ofFIG. 7 may be implemented by and/or executed on a single network device,such as network device 400 of FIG. 4. In other embodiments, process 700or portions of process 700 of FIG. 7 may be implemented by and/orexecuted on a plurality of network devices, such as network device 400of FIG. 4. In yet other embodiments, process 700 or portions of process700 of FIG. 7 may be implemented by and/or executed on one or more bladeservers, such as blade server 250 of FIG. 2B. However, embodiments arenot so limited and various combinations of network devices, bladeservers, or the like may be utilized.

In some embodiments, process 700 may be employed after process 500 or600 is employed. For example, in at least one embodiment, process 500may be employed to provide real time display of event records along withunique extracted values and their corresponding statistics. As describedin more detail below, in some embodiments, process 700 may enable a userto filter the display of the event records based on a selection of aunique extracted value.

Process 700 begins, after a start block, at block 702, where anextracted value may be selected from a plurality of displayed extractedvalues. In some embodiments, the selection may be of a unique extractedvalue, such as displayed at block 512 of FIG. 5 and/or 610 of FIG. 6. Inat least one of various embodiments, the selection of the extractedvalue may be received through a GUI. The GUI may be employed to enable auser to select the extracted value. In at least one embodiment, the usermay utilize a mouse or other pointing device to click on and select anextracted value. In some other embodiments, a user may select theextracted value by clicking on an identified value in an event record.However, embodiments are not so limited, and other mechanisms may beemployed to enable a user to select an extracted value.

Process 700 proceeds next to block 704, where a subset of the pluralityof event records may be determined based on the selected value. In atleast one embodiment, the subset of event records may include thoseevent records with a value (as extracted by the extraction rule) that isequal to and/or matches the selected value.

Process 700 continues at block 706, where the subset of event recordsmay be displayed. In at least one embodiment, block 706 may employembodiments of block 510 of FIG. 5 to display the filtered events basedon the extraction rule. For example, assume that 100 event records aredisplayed to a user (e.g., at block 510 of FIG. 5), where a valueextracted from each event record is highlighted in the event record. Ifa user selects extracted value “A”, then of the 100 event records, thoseevent records with an extracted value of “A” may be displayed to a user,such that any remaining event records may be hidden and/or otherwisedistinguished from the event records with the extracted value of “A”. Inat least one embodiment, those event records that do not include anextracted value that matches the selected value may be hidden from view.

Process 700 proceeds next at block 708, where a display of the extractedvalues may be modified based the selected value. In some embodiments,the selected value may be emphasized (e.g., by highlighting,underlining, and/or otherwise identifying the selected value. In otherembodiments, other extracted values (i.e., the non-selected value) maybe hidden, dimmed, or the like, to indicate that they were not selectedto determine the subset of event records.

After block 708, process 700 may return to a calling process to performother actions. In some embodiments, a user may be enabled to selectanother extracted value, in which case, process 700 may process thenewly selected extracted value. In other embodiments, the user mayde-select the selected value, which may re-display the extracted valuesfrom the plurality of event records.

It will be understood that each block of the flowchart illustration, andcombinations of blocks in the flowchart illustration, can be implementedby computer program instructions. These program instructions may beprovided to a processor to produce a machine, such that theinstructions, which execute on the processor, create means forimplementing the actions specified in the flowchart block or blocks. Thecomputer program instructions may be executed by a processor to cause aseries of operational steps to be performed by the processor to producea computer-implemented process such that the instructions, which executeon the processor to provide steps for implementing the actions specifiedin the flowchart block or blocks. The computer program instructions mayalso cause at least some of the operational steps shown in the blocks ofthe flowchart to be performed in parallel. Moreover, some of the stepsmay also be performed across more than one processor, such as mightarise in a multiprocessor computer system. In addition, one or moreblocks or combinations of blocks in the flowchart illustration may alsobe performed concurrently with other blocks or combinations of blocks,or even in a different sequence than illustrated.

Accordingly, blocks of the flowchart illustration support combinationsof means for performing the specified actions, combinations of steps forperforming the specified actions and program instruction means forperforming the specified actions. It will also be understood that eachblock of the flowchart illustration, and combinations of blocks in theflowchart illustration, can be implemented by special purposehardware-based systems, which perform the specified actions or steps, orcombinations of special purpose hardware and computer instructions.

Use Case Illustration

FIGS. 8A through 8C illustrate non-exhaustive examples of a use case ofembodiments of a graphical user interface that may be employed to enablea user to create extraction rule and to obtain real time display ofextracted values.

FIG. 8A illustrates a non-exhaustive example of a use case of anembodiment of graphical user interface that may be employed to enable auser to create extraction rule and to obtain real time display ofextracted values. Graphical user interface (GUI) 800A may includemultiple viewing windows and/or sections that each display informationto a user. For example, GUI 800A may include records 808, input 802,input 806, extraction rule preview 804, records 808, and extractedvalues 810.

Records 808 may display each event record that is determined based oninputs 802 and 806. Input 802 may enable a user to input a data source(e.g., a specific database) and/or a data type (e.g., system log data).As illustrated, input 802 may include one or more pull down menus ofavailable options of the data source and/or data type. However, othermenus, lists, windows, or interfaces may also be employed. Input 806 mayenable the user to define a specific filter to apply the event records(e.g., the user may filter the event records to display those eventrecords that were recorded on a particular day). In other embodiments,input 806 may enable a user to select how the event records are selectedfor display. In at least one embodiment, event records 808 may include asubset and/or sampling of a lager data set. For example, input 806 maybe used to select that event records 808 includes a predetermined number(e.g., 100) of the latest event records. However, other result types maybe used, such as oldest, most popular, least popular, or the like, orany combination thereof.

Extraction rule preview 804 may display instructions to a user forcreating an extraction rule. For example, the user may highlight and/orselect text in an event record in records 808 to have an extraction ruleautomatically created. In another example, the user may manually enteran extraction rule (e.g., by clicking on the “Create extraction rule”button, an editable text box may open or become visible where the usercan manually input an extraction rule). Extraction rule preview 804 maydisplay the extraction rule after it is created, such as is shown inFIG. 8B. Additionally, the user may be enabled to save the extractionrule for additional processing of event records and extracted values.

Extracted values 810 may show unique values that are extracted fromevent records 808 based on an extraction rule provided by extractionrule preview 804. As illustrated, extracted values 810 may be emptybecause no extraction rule has been provided.

FIG. 8B illustrates a non-exhaustive example of a use case of anembodiment of a graphical user interface where an extraction rule hasbeen provided. GUI 800B may be an embodiment of GUI 800A from FIG. 8A.

Extraction rule preview 804 may display the provided extraction rule. Inat least one embodiment, GUI 800B may include editable text box 814 toenable the user to provide a field name of the field defined by theextraction rule. As described above, the extraction rule may have beenautomatically generated based on user selected text from an event recordin the event records 808. In other embodiments, a user may have manuallyentered the extraction rule. As illustrated, the extraction rule may bedisplayed in editable text box 812. Editable text box 812 may enable auser to manually edit the extraction rule. As the user is manuallyediting the extraction rule, records 808 may be automatically anddynamically updated in real time to show new values extracted from eachevent record in records 808. For example, the extracted values from eachevent record may be highlighted or otherwise emphasized, as shown byhighlight 824. Additionally, extracted values 810 may be automaticallyand dynamically updated in real time as the user edits the extractionrule.

In other embodiments, the extraction rule may be manipulated byindicating an incorrect extracted value (e.g., a counter-example). In atleast one embodiment, a counter-example may be a value extracted from anevent record based on an extraction rule that does not match a desiredfield of the user. For example, assume an extraction rule is created todefine a field for a server name. However, assume the extraction ruleextracts other data from at least one of the event records. The user mayindicate this other data as a counter-example, and the system mayautomatically re-generate the extraction rule taking thiscounter-example into account. In at least one of various embodiments, auser may indicate a counter-example by clicking on a counter-examplebutton, such as button 822. By clicking button 822, the system mayautomatically re-generate the extraction rule based on the counterexample and the other extracted values.

Extracted values 810 may include one or more unique values extractedfrom records 808 based on the extraction rule. In at least oneembodiment, statistics that correspond to each unique extracted valuemay be displayed. For example, data 816 shows a percentage of the numberof times each particular unique value is extracted from records 808. Asillustrated, each of these percentages may also be illustrated as apercentage bar (e.g., percentage bar 818) for each unique extractedvalue.

FIG. 8C illustrates a non-exhaustive example of a use case of anembodiment of graphical user interface that may be employed to enable auser to select an extracted value to filter the event records. GUI 800Cmay be an embodiment of GUI 800A of FIG. 8A.

In at least one embodiment, a user may click on one or more valueswithin extracted values 810, such as value 820 to filter records 808.Records 808 may display those event records that include an extractedvalue that matches selected value 820. As illustrated, the display ofextracted values 810 may be modified to indicate which value wasselected by the user, such as by emphasizing the selected value and/orde-emphasizing the non-selected values.

FIGS. 9A and 9B illustrate a use case example of a real time display ofan event record based on manual editing of an extraction rule. Example900A illustrates extraction rule 902 and event record 904. Value 906 maybe highlighted, or otherwise emphasized, as a value extracted from eventrecord 904 based on extraction rule 902. Example 900B also illustratesextraction rule 902 and event record 904. However, as illustrated,extraction rule 902 may be manually edited by a user. Based on thisedited extraction rule, value 908 may be highlighted as a new valueextracted from event record 904 based on extraction rule 902.

The above specification, examples, and data provide a completedescription of the composition, manufacture, and use of the invention.Since many embodiments of the invention can be made without departingfrom the spirit and scope of the invention, the invention resides in theclaims hereinafter appended.

What is claimed is:
 1. A computer-implemented method, comprising:accessing a set of events in a field-searchable data store, wherein eachevent in the set includes a portion of raw machine data in textual form,and wherein the raw machine data reflects activity within an informationtechnology environment; applying an extraction rule, which specifies howto extract a subportion of text from a larger portion of text, to theportion of raw machine data in textual form in each event in theaccessed set of events to extract a set of values; for one or moreparticular values in the extracted set of values, determining aproportion of events that include the particular value at a locationcorresponding to the extraction rule; causing display of the one or moreparticular values concurrently with its associated proportion; andwherein the method is performed by one or more computing devices.
 2. Themethod of claim 1, wherein the field-searchable data store is searchableto reveal a performance or security of the information technologyenvironment based on the activity reflected by the raw machine data inthe data store.
 3. The method of claim 1, wherein the proportion is apercentage.
 4. The method of claim 1, wherein the proportion is a ratio.5. The method of claim 1, wherein the extraction rule at least in partdefines a field.
 6. The method of claim 1, wherein the extraction ruleat least in part defines a field, and the extracted set of valuesproduced by applying extraction rule to the accessed set of events aresemantically related.
 7. The method of claim 1, wherein the extractionrule at least in part defines a field that can be referenced in a searchquery by a name for the field.
 8. The method of claim 1, wherein a datastore of events is field-searchable when a search query containing acriterion for a field can be executed against the events in the datastore to cause comparison between the criterion and values extractedfrom the events by an extraction rule defining the field.
 9. The methodof claim 1, further comprising causing display of an indication of arelative rate of occurrence in events of different values from theextracted set of values.
 10. The method of claim 1, wherein causingdisplay of the one or more particular values concurrently with itsassociated proportion further comprises causing display of the one ormore particular values in a sorted order based on the associatedproportions.
 11. The method of claim 1, wherein the one or moreparticular values include only unique values found in the extracted setof values.
 12. The method of claim 1, wherein the extraction rule is aregular expression.
 13. The method of claim 1, wherein the extractionrule is a regular expression that has been automatically generated tocorrespond to a user-selected portion of raw machine data in aparticular event.
 14. The method of claim 1, further comprising: causingdisplay of at least one event having a given value in the extracted setof values at a location corresponding to the extraction rule; andcausing highlighting of the given value in the at least one displayedevent.
 15. The method of claim 1, further comprising: receiving inputcorresponding to a selection of a particular value that has beendisplayed with its associated proportion; based on receiving theselection, determining a subset of the set of events such that eachevent in the subset includes the selected particular value at a locationcorresponding to the extraction rule; and modifying a displayed set ofevents to include only events in the determined subset and to hide anyevents not in the determined subset.
 16. A non-transitory computerreadable storage medium impressed with computer program instructionsthat, when executed on a processor, implement a method comprising:accessing a set of events in a field-searchable data store, wherein eachevent in the set includes a portion of raw machine data in textual form,and wherein the raw machine data reflects activity within an informationtechnology environment; applying an extraction rule, which specifies howto extract a subportion of text from a larger portion of text, to theportion of raw machine data in textual form in each event in theaccessed set of events to extract a set of values; for one or moreparticular values in the extracted set of values, determining aproportion of events that include the particular value at a locationcorresponding to the extraction rule; causing display of the one or moreparticular values concurrently with its associated proportion; andwherein the method is performed by one or more computing devices. 17.The computer readable medium of claim 16, wherein the field-searchabledata store is searchable to reveal a performance or security of theinformation technology environment based on the activity reflected bythe raw machine data in the data store.
 18. The computer readable mediumof claim 16, wherein the proportion is a percentage.
 19. The computerreadable medium of claim 16, wherein causing display of the one or moreparticular values concurrently with its associated proportion furthercomprises causing display of the one or more particular values in asorted order based on the associated proportions.
 20. The computerreadable medium of claim 16, wherein the extraction rule is a regularexpression that has been automatically generated to correspond to auser-selected portion of raw machine data in a particular event.
 21. Thecomputer readable medium of claim 16, implementing the method furthercomprising: causing display of at least one event having a given valuein the extracted set of values at a location corresponding to theextraction rule; and causing highlighting of the given value in the atleast one displayed event.
 22. The computer readable medium of claim 16,implementing the method further comprising: receiving inputcorresponding to a selection of a particular value that has beendisplayed with its associated proportion; based on receiving theselection, determining a subset of the set of events such that eachevent in the subset includes the selected particular value at a locationcorresponding to the extraction rule; and modifying a displayed set ofevents to include only events in the determined subset and to hide anyevents not in the determined subset.
 23. A system including one or moreprocessors coupled to memory, the memory loaded with computerinstructions that, when executed on the processors, implement actionscomprising: accessing a set of events in a field-searchable data store,wherein each event in the set includes a portion of raw machine data intextual form, and wherein the raw machine data reflects activity withinan information technology environment; applying an extraction rule,which specifies how to extract a subportion of text from a largerportion of text, to the portion of raw machine data in textual form ineach event in the accessed set of events to extract a set of values; forone or more particular values in the extracted set of values,determining a proportion of events that include the particular value ata location corresponding to the extraction rule; causing display of theone or more particular values concurrently with its associatedproportion; and wherein the method is performed by one or more computingdevices.
 24. The system of claim 23, wherein the field-searchable datastore is searchable to reveal a performance or security of theinformation technology environment based on the activity reflected bythe raw machine data in the data store.
 25. The system of claim 23,wherein the proportion is a percentage.
 26. The system of claim 23,wherein causing display of the one or more particular valuesconcurrently with its associated proportion further comprises causingdisplay of the one or more particular values in a sorted order based onthe associated proportions.
 27. The system of claim 23, wherein theextraction rule is a regular expression that has been automaticallygenerated to correspond to a user-selected portion of raw machine datain a particular event.
 28. The system of claim 23, further implementingactions comprising: causing display of at least one event having a givenvalue in the extracted set of values at a location corresponding to theextraction rule; and causing highlighting of the given value in the atleast one displayed event.
 29. The system of claim 23, furtherimplementing actions comprising: receiving input corresponding to aselection of a particular value that has been displayed with itsassociated proportion; based on receiving the selection, determining asubset of the set of events such that each event in the subset includesthe selected particular value at a location corresponding to theextraction rule; and modifying a displayed set of events to include onlyevents in the determined subset and to hide any events not in thedetermined subset.